Research of Fault Diagnosis Based on Bayesian Network for Air Brake System

2010 ◽  
Vol 143-144 ◽  
pp. 629-633
Author(s):  
San Tong Zhang
Keyword(s):  
Fault Diagnosis ◽  
Bayesian Network ◽  
Network Model ◽  
Probabilistic Approach ◽  
Brake System ◽  
Bayesian Network Model ◽  
Diagnosis Model ◽  
Air Brake System ◽  
Test Result ◽  
Model Expression

A method for solving the fault diagnosis problem of air brake system based on probabilistic approach is presented. The fault diagnosis model based on Bayesian network was built for the uncertainty characteristic of fault in the air brake system. Through evaluating the characteristic of Bayesian networks in the diagnosis inference and model expression, it is demonstrated that this method can solve the uncertain problems in fault diagnosis. The test result has shown that the Bayesian network model is effective in fault diagnosis of the air brake system.

Probabilistic Model-Based Fault Diagnosis of the Rotor System

2007 ◽  
Author(s):  
Jiye Shao ◽  
Rixin Wang ◽  
Jingbo Gao ◽  
Minqiang Xu
Keyword(s):  
Fault Diagnosis ◽  
Bayesian Network ◽  
Network Model ◽  
Rotating Machinery ◽  
Rotor System ◽  
Bayesian Network Model ◽  
Diagnosis System ◽  
Model Based ◽  
Core Components ◽  
Fault Diagnosis System

The rotor is one of the most core components of the rotating machinery and its working states directly influence the working states of the whole rotating machinery. There exists much uncertainty in the field of fault diagnosis in the rotor system. This paper analyses the familiar faults of the rotor system and the corresponding faulty symptoms, then establishes the rotor’s Bayesian network model based on above information. A fault diagnosis system based on the Bayesian network model is developed. Using this model, the conditional probability of the fault happening is computed when the observation of the rotor is presented. Thus, the fault reason can be determined by these probabilities. The diagnosis system developed is used to diagnose the actual three faults of the rotor of the rotating machinery and the results prove the efficiency of the method proposed.

Bayesian Diagnostic Network Model for Sliding Plug Door

2011 ◽  
Vol 219-220 ◽  
pp. 1496-1499 ◽  
Author(s):  
Hui Chao Shi ◽  
Long Tian ◽  
Liang Wang
Keyword(s):  
Complex System ◽  
Fault Diagnosis ◽  
Expert System ◽  
Bayesian Network ◽  
Knowledge Base ◽  
Network Model ◽  
Model Building ◽  
Bayesian Network Model ◽  
Structure Tree ◽  
System Knowledge

For constructing Bayesian diagnostic network model of complex system is a difficult course, we propose a Bayesian network model auto-construction method based on expert system knowledge base. Bayesian diagnostic network model was built by using the CM structure, and the diagnostic knowledge was organized by product structure tree. We have applied this method to fault diagnosis for sliding plug door, and tested our methodology on many examples of diagnostic problems of sliding plug door, which prove the efficiency of the Bayesian diagnostic network model and model-building method．

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